VLDB 2026 Research / reviewers in the wild / expert
Daniel Gritzner
dblp:143/4723
· DBLP profile ↗
5ranked-venue papers
0as first author
0since 2021 · last 2018
0000-0001-6486-0008ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 4Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Requirements engineering and software design · 67% Programming languages and type systems · 33% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Embedded and real-time systems · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Requirements engineering and software design
reactive systems |
0.3 | 1 | 2017 | From scenario modeling to scenario programming for reactive systems with dynamic topology · ESEC/SIGSOFT FSE 2017 |
Programming languages and type systems › programming paradigms
scenario-based programming |
0.3 | 1 | 2017 | From scenario modeling to scenario programming for reactive systems with dynamic topology · ESEC/SIGSOFT FSE 2017 |
Requirements engineering and software design › specification
scenario-based specification |
0.3 | 1 | 2017 | From scenario modeling to scenario programming for reactive systems with dynamic topology · ESEC/SIGSOFT FSE 2017 |
Embedded and real-time systems
reactive systems |
0.1 | 1 | 2017 | From scenario modeling to scenario programming for reactive systems with dynamic topology · ESEC/SIGSOFT FSE 2017 |
Methods — techniques the papers use, named apart from their topics
scenario modeling language · 0.6code generation · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Towards Systematic and Automatic Handling of Execution Traces Associated with Scenario-based Models
Joel Greenyer, Daniel Gritzner, David Harel, Assaf Marron |
MODELSWARD | 2 |
| 2017 | Distributing Scenario-based Models: A Replicate-and-Project Approach
Shlomi Steinberg, Joel Greenyer, Daniel Gritzner, David Harel, Guy Katz, Assaf Marron |
MODELSWARD | 3 |
| 2017 | From scenario modeling to scenario programming for reactive systems with dynamic topologyabstractSoftware-intensive systems often consist of cooperating reactive components. In mobile and reconfigurable systems, their topology changes at run-time, which influences how the components must cooperate. The Scenario Modeling Language (SML) offers a formal approach for specifying the reactive behavior such systems that aligns with how humans conceive and communicate behavioral requirements. Simulation and formal checks can find specification flaws early. We present a framework for the Scenario-based Programming (SBP) that reflects the concepts of SML in Java and makes the scenario modeling approach available for programming. SBP code can also be generated from SML and extended with platform-specific code, thus streamlining the transition from design to implementation. As an example serves a car-to-x communication system. Demo video and artifact: http://scenariotools.org/esecfse-2017-tool-demo/ Joel Greenyer, Daniel Gritzner, Florian König, Jannik Dahlke, Jianwei Shi 0001, Eric Wete |
ESEC/SIGSOFT FSE | 2 |
| 2017 | ScenarioTools - A tool suite for the scenario-based modeling and analysis of reactive systems
Joel Greenyer, Daniel Gritzner, Timo Gutjahr, Florian König, Nils Glade, Assaf Marron, Guy Katz |
Sci. Comput. Program. | 2 |
| 2014 | GPU video retargeting with parallelized SeamCropabstractIn this paper, we present a fast parallel algorithm for the retargeting of videos. It combines seam carving and cropping and is aimed for real-time adaptation of video streams. The basic idea is to first find an optimal cropping path over the whole sequence with the target size. Then, the borders are slightly extended to be reduced again by seam carving on a frame-by-frame basis. This allows the algorithm to get more important content into the cropping window as it is also able to remove pixels from within the window. In contrast to the previous SeamCrop algorithm, the presented technique is optimized for parallel processes and a CUDA GPU implementation. In comparison, the computation time of our GPU algorithm is 10.5 times faster (on a 960 x 540 video with a retarget factor of 25%) than the already efficient CPU implementation. Johannes Kieß, Daniel Gritzner, Benjamin Guthier, Stephan Kopf, Wolfgang Effelsberg |
MMSys | 2 |